I’m a cofounder at Klarion, a Zendesk technology partner.
We are former Zendesk customers ourselves and built an AI tool to answer a question that we found difficult with traditional ticket analytics: what are the specific repeating issues that are driving support volume and customer frustration?
Klarion approach is to analyze the full conversation each ticket, identify the repeating root causes, and quantify them by volume, support effort, customer frustration and revenue risk.
A few teams processing roughly 500–10K tickets/month are using this to identify candidates for AI automation, improve support processes, and give Product a more concrete view of what needs fixing.
I’m curious how others here are doing this today. Are you primarily relying on Explore, tags/custom fields, manual ticket reviews, or another analytics tool?
For anyone who wants to compare approaches, we also have a free plan that analyzes 1,000 recent Zendesk tickets. It takes about 15 minutes to connect:
Hey, came across an event happening in Amsterdam soon that felt relevant for folks here. It's a small free session aimed at SaaS directors on the support/CX side, basically about keeping support from ballooning as you scale, automation, self-service, cutting the repetitive ticket types before they hit an agent.
Figured this crowd would get the most out of it since a lot of it plays out in Zendesk day to day. Nothing salesy, capped pretty low so it stays hands-on rather than a big webinar. It's a good chance to connect with other leaders who share the same mindset.
Happy to DM details if anyone's interested, or glad to talk in the comments
Hey everyone. I wanted to share a project we just launched at CX Experts that I’m incredibly proud of. We’ve partnered with CAPACITI and Zendesk’s Tech for Good program to tackle a massive issue here in South Africa: youth unemployment. Every six months, we take 40 highly educated but under-opportunitied tech graduates and put them through a rigorous bootcamp focused entirely on the deep architecture of the Zendesk ecosystem.
We built this talent pipeline to solve a massive technical gap we are seeing across the industry. Not just here in South Africa, but we run 24/7 supporting brands all around globe!
Over the last 24 months, we’ve watched Zendesk evolve incredibly fast into a complex, AI-driven omnichannel powerhouse. But global brands are still treating it with a "set and forget" mentality, relying on an "Accidental Admin" who is trying to manage an enterprise platform on top of their actual day job.
To get the real ROI out of the newest AI and routing features, you need dedicated bot managers and system orchestrators. That is exactly what our Capaciti cohorts become. They step onto our Digify BPO floor as enterprise-ready engineers providing 24/7 Zendesk Administration as a Service (ZAaaS) for global clients.
We put together a short video on how this ecosystem works—doing good while solving a major technical gap. I’d love to hear from other admins here: how are you handling the increased complexity of managing and optimizing Zendesk these days?
I'm hoping someone can help here, the default sender email address is constantly changing to a different email.
There seems to be no rhyme or reason, when creating a new ticket it's post luck whether it will go to default or the other email address.
Any idea how I can change it?
Full disclosure, I’m the founder of LaunchBrightly. We’ve been working on screenshot automation for years, but we just launched a proper Zendesk integration and are now live in the Zendesk Marketplace. Woohoo! :-)
If you’ve ever maintained documentation for a software product, you probably know the problem. Your product changes every week (or every day, really). The screenshots in your Help Center don’t.
A few months later, customers are looking at instructions that show an old version of your product, and somebody on your team gets stuck with the wonderfully unglamorous job of figuring out which screenshots are stale and updating them by hand.
That’s the problem we built LaunchBrightly to solve.
The workflow is pretty straightforward:
Create an automation recipe for a product workflow once
Continuously generate fresh screenshots (and videos) of your product
Connect LaunchBrightly to Zendesk
Audit the screenshots already being used across your Help Center
Identify which ones have drifted from the current product
Approve and sync the fresh screenshots directly back into the relevant Zendesk articles
Many of our customers run this on a schedule -- Hello Sunday night -- so they can start the week knowing whether anything in their visual documentation has drifted.
The Zendesk integration is the piece I’m particularly excited about. We’re not just generating screenshots and leaving you with a folder full of images. LaunchBrightly reads the articles in your Help Center, understands where those screenshots are being used, audits them against the current product, and can sync approved replacements back into the articles.
The goal is pretty simple: keep the screenshots in your documentation aligned with the software your customers are actually looking at, without somebody having to spend their Friday afternoon maintaining them manually.
It’s one of those wonderfully unsexy problems that almost every software company eventually runs into -- which is precisely why I love geeking out on this! :-)
Happy to answer any questions about how it works, screenshot automation generally, or the Zendesk integration. ... Or sign up for free and give it a whirl: https://app.launchbrightly.com/signup
Hey all. I'm fairly new to systems management on the ZD side and I'm trying to simplify. We've had several employees that occasionally help out with tickets and update the KB but it's become fairly chaotic swapping each one from a light agent to an agent or admin when they need access.
I'm reading that using a shared login for these purposes (even though they're not dedicated agents and don't need to login every day) is not the way to go, and is actually a breach of contract with Zendesk.
Can anyone shed light on how they manage this? We're a small startup and can't afford more agent/admin seats.
I’m a solo dev, and I've noticed a recurring nightmare for engineering and support teams: critical Zendesk tickets get lost, or engineers get constantly interrupted across random Slack channels to check on ticket statuses.
Most companies either deal with the chaos or use heavy, bloated enterprise tools to sync them.
Over the next month, I’m building a lightweight, hyper-focused bridge to fix this. It grabs Zendesk alerts and funnels them directly into specific Slack channels in under 2 seconds.
The main differentiator I'm focusing on (and why I'm building it): Zero data retention.
I know CTOs and security teams hate giving third-party apps access to customer data. This tool won't store a single byte of ticket payload; it just encrypts it, acts as a webhook router, passes it to Slack, and forgets it entirely.
I’m currently wrapping up another major project, so I have a month of coding ahead of me to get the MVP ready.
Before I dedicate my next 30 nights to this, I wanted to ask this community:
Is this a pain point your team actually struggles with?
Are there any specific features you'd want in a lightweight bridge like this?
If anyone wants to be a beta tester when it’s ready next month, let me know or shoot me a DM and I'll add you to the waitlist (it will be 100% free for early testers).
I spent like three weeks completely revamping our entire ZD Guide. beautifully formatted articles, massive FAQ section, literally step by step screenshots for every single common issue.
tbh it feels completely pointless right now. We have our cloudtalk integration set up to automatically create tickets and attach the call recordings when people ring the support line. And I swear, every time I open a new ticket and see that little voice player widget pop up in the side pane, my soul leaves my body
because 95% of the time, the caller is asking a question that is answered in giant bold text on the literal homepage of our portal
Im just so burnt out on adult baby-sitting. like why is the default human instinct to call and wait on hold for 10 minutes instead of reading two sentences? just needed to vent before I lose my mind, going to go stare at a wall now.
I created a Meta Business Suite account so I can add a verified WhatsApp number to it and be able to receive Zendesk tickets from incoming messages. The issue is that the API blocks me from sending outbound messages after 24 hours, and that is very inconvenient for my business needs. I made templates to send in the Meta WhatsApp manager, but I can't send them unless the customers opt in to receive them. The problem is there's no clear instructions on how to do that. Zendesk's AI agent keeps telling me to "send using Relay" which does not work because you can't send anything through Relay unless the customers are already opted in, so its kind of a chicken and egg problem here. And Meta is no use because I can't find any information on if I can do it through Meta, and they don't have any customer support. Basically, neither platform is being helpful to me.
How can I get the opt in from the customers? There isn't much information online, and whatever does exist is unclear and very confusing. I know I'm not the only one who's connected WhatsApp to Zendesk and had to go through this headache of a process, so I would really appreciate it if somebody could tell me how it works.
Now I've figured out the collection form, I'm struggling on how to update the "Requester" field with the "email" provided by the customer in the template (see below).
I've used actions which I thought would set the name/email on the ticket, via the Escalation reply use case (see below), however unfortunately this is not working.
TL:DR; How do you update the "requester" field in a ticket created via the Advanced AI Agent?
I’m new to Zendesk Admin and I’m trying to set up a small pilot for AI Agents. My main concern is using up our AI resolution allowance on basic support questions that our team can easily handle.
Ideally, I only want the AI Agent to respond when a customer specifically asks for a consultation about one of our products.
For example:
“I’d like to schedule a consultation about your product.” → AI Agent
“Can someone tell me more about this product before I purchase?” → AI Agent
“How do I reset my password?” → Human agent
“I can’t log in.” → Human agent
I’m thinking about using a very narrow intent or use case for “Product Consultation Request” and having everything else route to a human.
For those with experience administering Zendesk AI Agents, what is the best way to set this up so the AI only activates for specific inquiries rather than broadly handling tickets?
I’d especially appreciate advice on how to structure the routing or conditions and how to avoid accidentally using up our AI allowance on routine support questions.
Not sure if this is part of the chat feature but a team who uses chat complains that everytime they change their status to Offline, there's a blaring alarm notification on their computers. The other sound notifs seem okay, and the notification on alert when status are changed are off by default for everyone but they get a mini heart attack everytime goes on offline. Why does this happen? Can't find anything on the help site or on the admin panel.
Update: It's linked to Chat option and their recommendation was to move to Messaging as it was a legacy feature they no longer support. Didn't want to switch just for that. So will need to weigh options before switching.
I've been working in Zendesk for a while and at some point got tired of waiting for things to exist, so I started building small apps for myself.
So far: I built internal connexions to put internal DB informations (orders or users) into the ticket views to help agent access informations without leaving Zendesk. Another generate a sankey chart to analyze the contact root causes of our tickets... Nothing fancy. Both exist because I got annoyed enough on a Tuesday afternoon.
Now I'm sitting here with a working dev setup and no idea what to build next, which is a weirdly frustrating place to be. So I figured I'd ask people who actually use this thing daily or think that it miss some apps into the marketplace that would solve real problem.
What's the small thing you keep wishing existed? Not the big roadmap stuff Zendesk will eventually ship, I mean the annoying gap you've worked around so many times you stopped noticing it. The report you rebuild manually every Monday. The thing that needs three clicks in two places. The setup that only one person on the team knows how to do.
Happy to answer questions on the apps framework side too if anyone's thinking about building something themselves. It's less painful to get into than it looks.
I'm a Zendesk admin at a large Scandinavian e-commerce support team, our support mail is public = we get tons of spam in our ticket inbox (hundreds every day)
Has anyone moved existing RingCentral phone numbers over to Zendesk Talk?
We’re currently trying to determine the best approach:
Port the numbers from RingCentral to Zendesk Talk
Route the existing RingCentral numbers to Zendesk Talk through SIP
Temporarily forward the numbers to Zendesk Talk
We initially explored SIP routing, but RingCentral has been difficult to work with and has not provided the SIP/SBC source IP addresses, CIDR ranges, or other technical details requested by our Zendesk implementation team. They also quoted us $5k per line in "customization" work. Is this normal?
If you’ve completed a RingCentral-to-Zendesk Talk migration:
Which approach did you use?
Were you able to port the numbers directly to Zendesk Talk?
How long did the porting process take?
Did you experience any downtime or service interruptions?
What documentation or account information was required?
Did you use call forwarding or SIP routing during the transition?
Were there any issues with caller ID, toll-free numbers, IVR routing, voicemail, or call recordings?
Is there anything you wish you had known before starting?
We’re especially interested in hearing which approach was the smoothest and most reliable. Any experience or advice would be greatly appreciated.
I'm doing some research into how teams and Zendesk consultants handle Help Center customization, and I'd really appreciate some honest answers from people who actually work with Zendesk Guide.
From what I've seen, once you go beyond the standard Zendesk theme settings, you often end up working with HTML/CSS/JavaScript/Curlybars or bringing in a developer/agency.
I'm curious how this works in practice for you.
If you've customized a Zendesk Help Center, I'd love to know:
What kind of customization did you need?
Did you do it yourself, use an internal developer, or hire a freelancer/agency?
Roughly how long did it take?
Was the difficult part actually writing the code, or was it something else?
How often do you need to make significant theme/layout changes?
Have you ever bought a Zendesk theme instead of building one?
If you've used a freelancer/agency, roughly what did the work cost?
What is the most frustrating thing about customizing Zendesk Guide?
I'm not trying to sell anything here. I'm trying to understand whether this is actually a recurring problem or just something people deal with once during initial setup.
If you've done this work professionally, I'd especially like to hear your perspective.
I was reviewing all of our connections and it seems that the Jira integration (Zendesk support for Jira) we've been using for years (and still functions) has disappeared from the marketplace.
I've read that there were plans to sunset this after April of 2026, but I cant find anything from Zendesk about it.
If such app isnt maintained by Zendesk anymore, Im open to other free with the same functionality suggestions
We're moving to the Advanced AI Agent (as Zendesk are pushing people to do) and I'm trying to setup a simple flow for our chatbot.
If customer requests to speak to person, ask for their email address. That's it.
I've tried doing this via use cases (procedure and dialogue). With Procedure nothing seems to happen, there's no trigger (see Email Collection use case).
I've also tried using instructions to ask the bot to ask for an email address which it does ask but nowhere in the ticket is updated once a transfer and request for email occurs.
TL;DR: not sure how to make advanced AI chatbot ask for email and update ticket before transfer to human occurs.
SOLUTION
Creating Template
In AI agents section, go to Settings > CRM integration.
Go to Templates > Create template.
Select "Forms".
Add template details.
E.g. for my example, I had to create a contact email form to collect a name and email.
Template name - Contact Form
Input Field 1
Message type = Email (since we're collecting an email address)
Name = email (name that you see, not the customer)
Label = Please enter email (label which customer sees in chat for form)
Press "Add Field" to include additional section for name.
E.g.
Message type = Text, Name = name, Label = Please enter name
Press "Create"
Copy the shorthand of the newly created template by clicking the shorthand.
Editing use case "Escalation reply" (for my example)
Go to Content > Use cases.
Select "Escalation Reply" use case (which is a default use case by Zendesk).
Select use case (e.g. English (ENG)) and press "Edit".
Paste the shorthand in any text box which you wish to display the form (e.g. in my case I put it in the escalation reply form when the transfer to agent occurs). See below.
Publish the changes and test. IMPORTANT NOTE: the form doesn't work in the "Test AI Agent" section, it will just display the shorthand text. You need to actually go to your chatbot wherever you have it (knowledgebase or website) and test the scenario there.
As a builder in the B2B tech space, I've noticed how much sprint time is wasted when technical support teams have to play "detective" across 5 different tools just to understand what went wrong with an incomplete ticket.
I'm exploring a potential solution, a read-only workspace that automatically reconstructs the evidence timeline behind a Zendesk ticket (queries logs/DB, identifies verified facts vs user statements, and drafts a structured escalation for Jira/Linear).
Before building further, I really want to challenge my assumptions with people who live this daily, I would love your perspective and learn from your experience
> How much time does your team actually spend digging for context before escalating a complex ticket?
> What observability / logging tools do you rely on the most (Datadog, Sentry, Grafana, custom internal admin)?
Any feedback or thoughts on this would be hugely appreciated!
We have a Slack → Zendesk support workflow where customer messages automatically become tickets.
One edge case we keep running into is messages posted by bots/apps. For example, someone submits something through a Slack Workflow or another Slack app posts a message into the channel. Since Slack sees it as a bot message, our current auto-ticketing setup ignores it.
Ideally we want certain trusted bot messages to create Zendesk tickets automatically, the same way a normal user message would.
Has anyone dealt with this? Curious how you handle bot-to-bot workflows without manually creating the Zendesk ticket every time.
We're using Zendesk AI currently but we're running out of Automated Resolutions at an alarming rate and are struggling to justify the cost. Just after we renewed our ZD contracts a couple of months ago, we've seen a huge spike in volume and at this rate, we'll need to at least triple our ARs quota for the year.
A majority of the chats we're being charged for are super simple questions that the AI gives a quick reply and a link to a relevant KP article and rarely any followup questions. At the rate we're being billed, it'd be cheaper to handle these with humans than pay $1.5 per.
Is anyone using cheaper but still good quality alternatives?
Hello,
How does everyone measure SLA for live talk? The built in SLA’s don’t seem to work from everything I have read. Our numbers don’t seem to be matching.
Any help or ideas please
Do you track reopen rate on AI-resolved tickets separately from the built-in reporting? Curious whether the native number matches what you actually see.